AI EDGE
AI Edge Computing
Local intelligence for perception, navigation, decision-making, and real-time embedded deployment.
Explore Quatomix sensing, positioning, control, AI Edge computing, UAV, and sensor-fusion platforms.
Integrated technologies for sensing, navigation, perception, decision-making, control, and AI acceleration at the edge.
Quatomix does not add intelligence to hardware as an afterthought. The complete system is designed around measurable machine intelligence.
Local intelligence for perception, navigation, decision-making, and real-time embedded deployment.
Reliable machine awareness through timestamping, calibration, filtering, covariance, and redundancy.
RTK, PPK, timing, hybrid localization, dead reckoning, and GPS-denied navigation support.
Control algorithms that convert perception and decisions into stable, measurable physical behavior.
Ultra-efficient intelligence at the sensor edge for anomaly detection, monitoring, and adaptive sensing.
Hardware-aware AI models optimized for embedded latency, memory, throughput, and thermal behavior.
Adaptive decision intelligence for planning, navigation, energy management, task allocation, and learning-assisted control.
MCU, SoC, SoM, NPU, GPU, FPGA, and hybrid architectures selected around workload, latency, data movement, and energy efficiency.
Real-time supervision, TinyML, sensing, low-power event detection.
Embedded Linux, device management, connectivity, AI coordination.
Validated modules, scalable compute tiers, faster carrier-board development.
Efficient neural inference for detection, segmentation, and continuous AI.
Flexible parallel acceleration for perception, vision, and deep learning.
Deterministic dataflow, interface timing, preprocessing, post-processing.
FPGA allows Quatomix to design computing pipelines around the data itself: capture, synchronize, preprocess, infer, post-process, and control output.
Perception, localization, motion control, SLAM, RL, TinyML monitoring, and real-time firmware.
GNSS, RTK, multi-IMU fusion, visual/LiDAR odometry, AI mission compute, flight control.
TinyML, NPU inference, anomaly detection, predictive monitoring, intelligent gateways.
Heterogeneous computing, multi-sensor fusion, AI planning, adaptive control, diagnostics.
Physical task, environment, constraints, targets, and failure conditions.
Sensors, compute, accelerators, firmware, software, and AI methods.
Timing, noise, bias, data quality, variability, and sensor behavior.
Fusion, control, ML, DL, RL, and signal-processing algorithms.
Memory, precision, operators, dataflow, scheduling, and runtime.
Hardware, firmware, AI models, sensors, and control systems.
Nominal, edge, rare, and failure conditions in repeatable scenarios.
SIL, HIL, bench testing, and real-platform testing.
Latency, accuracy, power, thermal behavior, robustness, and recovery.
Production releases, updates, diagnostics, lifecycle, and optimization.
AI Edge, sensing, navigation, control, embedded AI, and heterogeneous computing.
Download BrochureMCU, SoC, SoM, NPU, GPU, FPGA, and hybrid deployment architectures.
Download GuideIMU, GNSS, visual, LiDAR, encoder, and multi-sensor estimation architectures.
Download BriefNPU, GPU, FPGA, and hybrid accelerator strategies for robotics and UAVs.
Download GuideLow-power ML deployment, model optimization, and MCU-level intelligence.
Download BriefControl algorithms, RL, planning, and intelligent decision architectures.
Download GuideWhether your project needs precision navigation, sensor fusion, real-time control, TinyML, deep learning, reinforcement learning, or a custom AI accelerator, Quatomix can help define and build the complete architecture.